Using functors to memoize a function in R.

functor_memoization.R

## Functor example 1: Memoization. 
## We memoize a function g with up to N values.

## The function to memoize: It is slow to calculate, so we'll gain from 
## storing its values.

g = function(x) {
    Sys.sleep(0.1)
    print("Processesing ...")
    x^2
}

## The setup that does the memoization. It will store up to precompute_N values,
## starting over when the edge is met. More sophisticated methods are possible.

precompute_N = 100

f = function(x) {
      ## Memoize values:
      if(x %in% f$precomputed_names) {
        index = which(x == f$precomputed_names)
        return(f$precomputed[[index]])
      }

      y = g(x)
      
      precomputed_index = (f$precompute_index + 1) %% precompute_N
      f$precompute_index = precomputed_index
      f$precomputed[[precomputed_index]] = y
      f$precomputed_names[[precomputed_index]] = x
      
      y
}

class(f) = "f"

## We will need some generics and some members of the f-environment. 

`$.f` = function(f, y) environment(f)[[y]]

`$<-.f` = function(f, y, value) {
  environment(f)[[y]] = value
  invisible(f)
}


environment(f) = new.env()
environment(f)$precomputed = as.list(rep(NA, precompute_N))
environment(f)$precomputed_names = as.list(rep(NA, precompute_N))
environment(f)$precompute_index = 0

## Testing:

f(3)
f(3)
f(3)

f(5)
f(5)
f(5)

f(7)
f(7)
f(7)